Tsjarly

- Jul 24, 2024
- Joined Oct 3, 2023
- 1 best answer
Hi @jakaskerl,
To be clear, the ToF and the stereo are separate devices. and for the stereo, we had 2 devices where one worked fine and the other one showed the glare. Could it be that one of them had the IR-CUT filter installed? And is this something we can install ourselves somehow?
Hi @erik ,
That makes sense, was just wondering if there were some plans to tackle some of the noise filtering indeed. I feel like some temporal filtering might already solve some issues. The paper looks interesting, will also have a look at that and see if we can try something offline for now. Thanks!
oh whoops, the ToF error was because the usb one was still plugged in as well, but gave the same error as the stereo one before.
[14442C1051F939D100] [169.254.1.222] [6.636] [system] [critical] Fatal error. Please report to developers. Log: 'PlgSrcCtrl' '87' [14442C1051F939D100] [169.254.1.222] [1720017377.286] [host] [warning] Device crashed, but no crash dump could be extracted. Traceback (most recent call last): File "/home/jarl/Desktop/VBTI projecten/Depth AI/v2.26/depthai-python/examples/ImageAlign/record_images_with_tof.py", line 306, in <module> messageGroup = queue.get() RuntimeError: Communication exception - possible device error/misconfiguration. Original message 'Couldn't read data from stream: 'out' (X_LINK_ERROR)'
Hi @jakaskerl
I tried this, but it breaks both the pipelines for the ToF camera as well as the stereo pair.
For the ToF I get this output:
[19443010F12E9B2E00] [1.1] [11.098] [ToF(1)] [error] Unexpected input image size 1280 x 800, maybe connected camera is not ToF?
and for the stereo:
[19443010F12E9B2E00] [1.1] [0.811] [system] [critical] Fatal error. Please report to developers. Log: 'PlgSrcCtrl' '87' [19443010F12E9B2E00] [1.1] [1720016479.587] [host] [warning] Device crashed, but no crash dump could be extracted. Traceback (most recent call last): File "record_images.py", line 192, in <module> record_images(args) File "record_images.py", line 68, in record_images input_images = {name: queue.get().getCvFrame() for name, queue in queues.items()} File "record_images.py", line 68, in <dictcomp> input_images = {name: queue.get().getCvFrame() for name, queue in queues.items()} RuntimeError: Communication exception - possible device error/misconfiguration. Original message 'Couldn't read data from stream: 'depth' (X_LINK_ERROR)'
I also noticed that there was a comment on the blogpost you linked that mentions it only works for rgb cam only usage, which is not our use case unfortunately. Is there a workaround for this to still get the aligned/synced ToF/stereo depth in combination with the custom tuning?
Hi,
I noticed that for the ToF config in the pipeline there is no option to do postprocessing filtering (for example max/min thresholding, spatial filtering, temporal filtering) which you can do for the stereo Node. Is this something that is still in the works, or will this not be possible anytime in the future, if possible at all.
Kind regards,
JarlDid another test by using the camtest.py script, and pumping up the IR flood to max while watching with the other camera, and it is clearly an Infra Red issue. Is this somehow solveable with software / settings, or is this a hardware issue?
We tried to take some images in a greenhouse environment today, but saw that multiple of the oak cameras which use the OV9782 sensor had a purple glare over the rgb image.
We used 2 oak-d-pro cameras with the same pipeline, aimed at the same position, where one output had the glare, and the other was perfectly fine.
We also tested the Oak-d SR ToF, where both rgb sensors had this purple glare.
In normal outdoor or office conditions it looks fine, but deeper into the greenhouse the effect got worse.It is also not a uniform distributed issue as it gets pinker more towards the edges, and less of a problem in the center of the image. Based on other forumposts, we have the idea that there is something wrong with the IR filtering (or perhaps uv light?). We tried to set the exposure time in different ranges, but this did not effect the glare at all. Any idea what is going on or how to tackle this?
Hi,
When running the ToF depth alignment example, we get the output resolution of 640x400, which is the resolution of the depth sensor. Is it possible to get an aligned output with the resolution of the RGB camera?
Thank you,
JarlWhen we run the tof depth script we get this output, which visually looks nice! In this example we have aimed it at the wall at approximately 62 cm, but if we print the value of depth_map from the wall it returns a value around 360 (mm?). So before it is colorized. Is this supposed to be the absolute depth, or should we do anything to obtain the absolute values from here?
We now managed to get both rgbs working (was an issue with vs code and dependencies). But it would still be nice if you'd already have an example script where rgb and ToF depth are connected / aligned / synced
I do notice that the cam_test opens up the ToF plot and two grayscale mono plots, whereas they are rgb sensors, right?
Note that when I run cam_test it finds both sockets, as well as ToF
Hi,
We received a Oak-D SR PoE today, and the example depth script looks very promising. Do you also have an example already where the rgb is linked / aligned to the ToF?
We are trying to connect to the rgb's ourselves, but it mentions that the Camera is not detected on Socket: 2 (when trying to link it to socket_C). It works for the one on Socket_B
@jakaskerl
Okay, will do, thank you for looking with me!- Edited
Is EEPROM available: True User calibration: { "batchName": "", "batchTime": 1685789180, "boardConf": "IR-C11M08-00", "boardCustom": "", "boardName": "DM9098", "boardOptions": 1048580, "boardRev": "R6M2E6", "cameraData": [ [ 2, { "cameraType": 0, "distortionCoeff": [ -9.593585968017578, 77.64874267578125, -0.004904373548924923, 0.005081276409327984, -105.01581573486328, -9.663439750671387, 77.65552520751953, -104.79251861572266, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], "extrinsics": { "rotationMatrix": [ [ 0.9998430609703064, 0.007657993119210005, 0.015974950045347214 ], [ -0.007840709760785103, 0.999904215335846, 0.011406615376472473 ], [ -0.01588606834411621, -0.011530079878866673, 0.9998072981834412 ] ], "specTranslation": { "x": 3.75, "y": 0.0, "z": 0.0 }, "toCameraSocket": 0, "translation": { "x": 3.733102560043335, "y": -0.06864699721336365, "z": 0.012714797630906105 } }, "height": 800, "intrinsicMatrix": [ [ 804.4902954101562, 0.0, 666.06103515625 ], [ 0.0, 798.3745727539062, 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255, 255, 255, 255, 255, 79, 65, 75, 45, 68, 45, 80, 82, 79, 45, 70, 70, 45, 57, 55, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 73, 82, 45, 67, 49, 49, 77, 48, 56, 45, 48, 48, 0, 0, 0, 0, 70, 49, 45, 70, 86, 48, 48, 45, 66, 67, 48, 48, 49, 0, 0, 0, 77, 97, 120, 119, 101, 108, 108, 0, 0, 0, 0, 0, 0, 0, 0, 0, 252, 25, 123, 100, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 16, 0, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255] Factory calibration raw: [7, 0, 170, 85, 3, 0, 0, 0, 0, 68, 77, 57, 48, 57, 56, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 82, 54, 77, 50, 69, 54, 0, 0, 0, 0, 81, 250, 127, 63, 91, 63, 180, 187, 178, 14, 68, 188, 37, 203, 180, 59, 241, 254, 127, 63, 52, 67, 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160, 60, 63, 8, 175, 189, 0, 0, 240, 192, 0, 0, 0, 0, 0, 0, 0, 0, 2, 32, 3, 0, 5, 0, 151, 114, 69, 68, 0, 0, 0, 0, 120, 136, 37, 68, 0, 0, 0, 0, 151, 114, 69, 68, 33, 98, 197, 67, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 128, 63, 116, 79, 222, 63, 65, 81, 90, 65, 240, 5, 49, 58, 218, 160, 45, 186, 71, 124, 190, 193, 112, 173, 195, 63, 147, 205, 102, 65, 70, 216, 195, 193, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 82, 184, 143, 66, 0, 2, 20, 247, 127, 63, 157, 209, 12, 60, 97, 201, 102, 60, 172, 156, 14, 188, 144, 251, 127, 63, 251, 51, 253, 59, 209, 174, 101, 188, 216, 151, 0, 188, 139, 247, 127, 63, 168, 62, 112, 64, 114, 215, 71, 189, 28, 105, 173, 188, 0, 0, 112, 64, 0, 0, 0, 0, 0, 0, 0, 0, 0, 32, 3, 0, 5, 0, 44, 84, 70, 68, 0, 0, 0, 0, 129, 149, 25, 68, 0, 0, 0, 0, 44, 84, 70, 68, 69, 95, 199, 67, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 128, 63, 251, 155, 36, 193, 214, 56, 175, 66, 138, 105, 153, 58, 195, 250, 209, 57, 94, 8, 241, 193, 247, 253, 36, 193, 204, 1, 174, 66, 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hi @jakaskerl
I get the results above from the calibration dump@jakaskerl oh sorry, only see this post now, what do you mean exactly with calibration dump?
Hi @jakaskerl
I get the above output when running cam_test, and the image output is the same, also right cam not working.